A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions

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A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions (2009)

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by Zhihong Zeng , Maja Pantic , Glenn I. Roisman , Thomas S. Huang

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374 - 51 self

BibTeX

@MISC{Zeng09asurvey,
    author = {Zhihong Zeng and Maja Pantic and Glenn I. Roisman and Thomas S. Huang},
    title = {A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions},
    year = {2009}
}

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Abstract

Automated analysis of human affective behavior has attracted increasing attention from researchers in psychology, computer science, linguistics, neuroscience, and related disciplines. However, the existing methods typically handle only deliberately displayed and exaggerated expressions of prototypical emotions, despite the fact that deliberate behavior differs in visual appearance, audio profile, and timing from spontaneously occurring behavior. To address this problem, efforts to develop algorithms that can process naturally occurring human affective behavior have recently emerged. Moreover, an increasing number of efforts are reported toward multimodal fusion for human affect analysis, including audiovisual fusion, linguistic and paralinguistic fusion, and multicue visual fusion based on facial expressions, head movements, and body gestures. This paper introduces and surveys these recent advances. We first discuss human emotion perception from a psychological perspective. Next, we examine available approaches for solving the problem of machine understanding of human affective behavior and discuss important issues like the collection and availability of training and test data. We finally outline some of the scientific and engineering challenges to advancing human affect sensing technology.

Keyphrases

spontaneous expression human affective behavior affect recognition method test data prototypical emotion paralinguistic fusion audio profile human affect analysis available approach multimodal fusion audiovisual fusion body gesture related discipline visual fusion engineering challenge computer science facial expression exaggerated expression visual appearance paper introduces recent advance machine understanding deliberate behavior differs head movement human emotion perception discus important issue psychological perspective

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